(a) Find the second derivatives of f(x)=∫_-∞^x^2 / 2 e^x-t^2 / 2 d t and g(x)=∫_-∞^x^2
- (a) Find the second derivatives of \(f(x)=\int_{-\infty}^{x^{2} / 2} e^{x-t^{2} / 2} d t\) and \(g(x)=\int_{-\infty}^{x^{2} / 2} e^{-\left(x^{2}+1\right) t^{2}} d t\).
(b) Derive the solution of the ordinary differential equation
\[\frac{d^{2} y}{d x^{2}}=f(x), \quad x>0, \quad y(0)=0, \quad \frac{d y}{d x}(0)=0\]
in the form
\[y(x)=\int_{0}^{x}(x-t) f(t) d t\]
(c) Find the three second partial derivatives of \(f(x, y)=e^{-\frac{(x-1)^{2}-(y+1)^{2}}{2}}\).
Problem 2: Consider the partial differential equation
\[\frac{\partial u}{\partial t}=\frac{\partial^{2} u}{\partial x^{2}}\]
By assuming a solution of the form \(u(x, t)=X(x) T(t)\), deduce that
\[u_{\alpha}(x, t)=\left(A_{\alpha} \cos (\alpha x)+B_{\alpha} \sin (\alpha x)\right) e^{-\alpha^{2} t}\]
where \(A_{\alpha}\) and \(B_{\alpha}\) are constants, is a solution for any constant \(\alpha\). Show that if we now impose the boundary conditions \(u(0, t)=0, u(\pi, t)=0\), then this reduces the possible solutions to those of the form
\[u_{n}(x, t)=B_{n} \sin (n x) e^{-n^{2} t}\]
for \(n=0,1,2, \ldots\) and where \(B_{n}\) is a constant. Hence or otherwise find the solution of the
problem
\[\begin{aligned}
& \frac{\partial u}{\partial t}=\frac{{{\partial }^{2}}u}{\partial {{x}^{2}}},\quad u(0,t)=0,\quad u(\pi ,t)=0 \\
& u(x,0)={{\sin }^{2}}(x),\quad 0<x<\pi \\
\end{aligned}\]
Problem 3: By considering \(S_{n}=1+x+x^{2}+\cdots+x^{n}\), or otherwise, show that for \(|x|<1\)
\[\frac{1}{1-x}=1+x+x^{2}+x^{3}+x^{4}+x^{5}+\cdots\]
Use this result to find the Taylor series of the functions below and indicate the values of \(x\) for which the corresponding series converges:
\[\text { (a) } \frac{1}{2-x}, \quad \text { (b) } \frac{x}{1+x-2 x^{2}}, \quad \text { (c) } \log \left(\frac{1+x}{1-x}\right) \text { . }\]
Problem 4:
For the following matrix, find all eigenvalues and all (normalised) eigenvectors:
\[\left(\begin{array}{ccc}
6 & -2 & 2 \\
-2 & 5 & 0 \\
2 & 0 & 7
\end{array}\right)\]
Problem 5: Solve the following ordinary differential equation initial value problems for \(y(x)\)
- \[{{y}^{\prime }}+xy=0,\quad y(0)=1\text{ , }\]
- \(x^{2} y^{\prime \prime}-4 x y^{\prime}+6 y=6, \quad y(1)=0, y^{\prime}(1)=1\),
- \(y^{\prime \prime}+y^{\prime}-6 y=1, \quad y(0)=0, \quad y^{\prime}(0)=2\)
Problem 6: For the following functions, find the critical points, determine their nature (maxima, minima, inflection, etc.) and sketch the graph or surface:
- \(f(x)=\frac{x}{1+x^{2}}\) for \(x \neq 0\),
- \(\quad g(x)=|x| e^{-|x-1|}\),
- \(\quad F(x, y)=\left(x^{2}-4\right)^{2}+y^{2}\),
- \(\quad G(x, y)=\sin x \sin y \sin (x+y) \quad(0 \leq x, y \leq \pi)\).
Problem 7:
Consider the heat equation
\[\frac{\partial u}{\partial t}=\frac{\partial^{2} u}{\partial x^{2}}\]
Show that if \(u(x, t)=t^{\alpha} \phi(\xi)\) where \(\xi=x / \sqrt{t}\) and \(\alpha\) is a constant, then \(\phi(\xi)\) satisfies the ordinary differential equation
\[\alpha \phi-\frac{1}{2} \xi \phi^{\prime}=\phi^{\prime \prime}\]
(where \(\prime \equiv d/d\xi \) ). Show that
\[\int_{-\infty}^{\infty} u(x, t) d x=\int_{-\infty}^{\infty} t^{\alpha} \phi(\xi) d x\]
is independent of \(t\) only if \(\alpha=-\frac{1}{2}\). Further, show that if \(\alpha=-\frac{1}{2}\) then
\[C-\frac{1}{2} \xi \phi=\phi^{\prime}\]
where \(C\) is an arbitrary constant. From this last ordinary differential equation, and assuming \(C=0\), deduce that
\[u(x, t)=\frac{A}{\sqrt{t}} e^{-x^{2} / 4 t}\]
is a solution of the heat equation (here \(A\) is an arbitrary constant).
Show that as \(t\) tends to zero from above,
\[\lim _{t \rightarrow 0+} \frac{1}{\sqrt{t}} e^{-x^{2} / 4 t}=0 \text { for } x \neq 0\]
and that for all \(t>0\)
\[\int_{-\infty}^{\infty} \frac{1}{\sqrt{t}} e^{-x^{2} / 4 t} d x=B\]
where \(B\) is a (finite) constant. Given that \(\int_{-\infty}^{\infty} e^{-x^{2}} d x=\sqrt{\pi}\), find \(B\).
What physical and/or probabilistic interpretation might one give to this solution \(u(x, t)\) ?
Problem 8: Let \(X_{1}, X_{2}, \ldots, X_{n}\) be independent, identically distributed random variables, each having a distribution function \(F_{X}(x)\). Let \(M=\min \left\{X_{1}, X_{2}, \ldots, X_{n}\right\} .\) Find the distribution function of \(M\). Now suppose \(F_{X}\) is the uniform distribution over \((0,1)\). What is the probability density function of \(M\) ?
10. Let \(X\) and \(Y\) be random variables with joint probability density
\[f_{X, Y}(x, y)=\left\{\begin{array}{cl}
c e^{-x-y}, & 0<x<y<\infty \\
0 & \text { otherwise. }
\end{array}\right.\]
Determine the value of the constant \(c\). Determine whether \(X\) and \(Y\) are independent.
11. A gambler plays a game in which there is a probability \(p\) of winning one unit and probability \(q=1-p\) of losing one unit. Successive plays of the game are independent. What is the probability that, starting with \(x>0\) units, the gambler's fortune will reach N? If \(p=q\) find the expected time for a gambler who starts with \(x>0\) units to lose them all.
12. Let \(X\) and \(Y\) have a bivariate normal distribution.
- Show that \(X\) and \(Y\) are normally distributed, and find their mean and variance.
- Show that \(X+Y\) is normally distributed, and find its mean and variance.
Problem 13: The random variable \(Y\) has the standard normal density with mean 0 and variance 1 , \(Y \sim \mathcal{N}(0,1)\). Find the distribution and density functions of \(V=Y^{2}\)
The moment generating function \(M_{X}(t)\) of a random variable \(X\) is defined by \(M_{X}(t)=\) \(E\left[e^{t X}\right] .\) If \(X \sim \mathcal{N}(0,1)\), show that \(M_{X}(t)=e^{t^{2} / 2}\)
Let \(X\) and \(Y\) be independent standard normal random variables, and \(Z=X Y\). Find \(M_{Z}(t)\), either by direct calculation or via the tower law in the form \(E\left[e^{t Z}\right]=\) \(E\left[E\left[e^{t Z} \mid Y\right]\right]\)
Problem 14: A hen lays \(N\) eggs, where \(N\) has the Poisson distribution with parameter \(\lambda\). Each egg hatches with probability \(p\) independently of the other eggs. Let \(K\) be the number of chicks.
- Find the expected number of chicks given that \(N=n\).
- Find the expected number of chicks.
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